Results 81 to 90 of about 20,444,239 (288)
Long-Term Evaluation of Drivers' Behavioral Adaptation to an Adaptive Collision Avoidance System. [PDF]
Muslim H, Itoh M.
europepmc +1 more source
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
RETRACTED: Improvement in Collision Avoidance in Cut-In Maneuvers Using Time-to-Collision Metrics
This paper proposes a new strategy for a collision avoidance system leveraging time-to-collision (TTC) metrics for handling cut-in scenarios, which are particularly challenging for autonomous vehicles (AVs).
Jamal Raiyn
doaj +1 more source
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka +3 more
wiley +1 more source
Path design and receding horizon control for collision avoidance system of cars [PDF]
The paper deals with path design and control realization problems of collision avoidance systems (CAS) of cars (ground vehicles). CAS emergency path design is based on the principle of elastic band with improved reaction forces for road borders and ...
Lantos, Béla
core +1 more source
In multi-vessel collision avoidance decision-making, the collision between merchant and fishing vessels is a significant challenge. This paper proposes a fuzzy fusion method for making avoidance decisions under the influence of the navigation environment.
Xudong Gai +3 more
doaj +1 more source
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao +4 more
wiley +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source
LLM‐Integrated Human–Robot Interaction System for Microrobots
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source
In recent years, an automatic collision avoidance system has been put into practical use by various automotive companies. In this study, we propose an automatic collision avoidance system for a four-wheel independent drive vehicle using the state ...
Naoto YOSHIDA +3 more
doaj +1 more source

